geiger (version 1.2-13)

dtt: Disparity-through-time

Description

Functions for calculating and plotting disparity-through-time for a phylogenetic tree and phenotypic data.

Usage

disp.calc(data, disp = "avg.sq")
dtt(phy, data, data.names=NULL, disp = "avg.sq")
dtt.full(phy, data, data.names=NULL, disp="avg.sq", nsims=1000, mdi.range=c(0,1))

Arguments

data

Data matrix - either actual or simulated

data.names

Tip names for data vector that match tree species; ignored if data includes names

phy

Phylogenetic tree in 'phylo' format

disp

Disparity measure: see below for currently implemented options.

nsims

Number of simulations used to calculate null dtt plot

mdi.range

Time range over which to calculate MDI statistic (area between curves). Time is relative to the total tree length of 1; default is the whole tree from 0 (root) to 1 (tips)

Value

• disp.calc
  Disparity of the supplied data
• dtt
  Average disparity for clades whose stem crosses each time interval in the tree.
• dtt.full
  A list with the following items: dtt.data{DTT for the data} dtt.sims{DTT for each simulated data set} times{Times for each value in the dtt plot; this is just the branching times of the phylogeny} MDI{Value of the MDI statistic, which is the area between the DTT plot for the data and the mean of the simulations} Plot{Creates a DTT plot}

Details

The most complete function, dtt.plot, carries out the entire disparity-through-time procedure described in Harmon et al. 2003. Other functions are for various parts of this, as follows: disp.calc{Calculate morphological disparity for a set of species. Disparity measure can be one of the following: avg.sq{Average squared euclidean distance among all pairs of points. This is a good choice if all of the axes are in the same units, or PC axes.} avg.manhattan{Average Manhattan distance among all pairs of points. This is a good choice if the axes are all in different units, like colors and lengths.} nb.states{Number of unique character states; this is the only option for discrete character data, for now.} } dtt{Evaluates disparity-through-time for either a single data set or multiple data sets (for example, from simulations).} dtt.full{Calculates dtt for the actual data, runs simulations using univariate or multivariate Brownian motion, calculates dtt for all simulations and finds the mean, and plots dtt for both data and simulations on the output device.}

References

Foote, M. 1997. The evolution of morphological diversity. Annual Review of Ecology and Systematics 28:129-152. Harmon, L. J., J. A. Schulte, J. B. Losos, and A. Larson. 2003. Tempo and mode of evolutionary radiation in iguanian lizards. Science 301: 961-964.

Examples

data(geospiza)
attach(geospiza)

disp.calc(geospiza.data)
disp.data<-dtt(geospiza.tree, geospiza.data)
full.output<-dtt.full(geospiza.tree, geospiza.data)